Glenn Roe

Text Mining Electronic Enlightenment: Influence and Intertextuality in the Eighteenth-Century Republic of Letters

Dr Glenn Roe (Mellon Fellow in Digital Humanities at Oxford’s OERC) describes the latest digital approaches to long-form historical texts. Roe starts out by observing the irony that the recent efflorescence of big data, culturomics, network analysis, and other quantitative approaches to culture – focusing in many cases on the macro interpretation of metadata over content – has authorized and promoted a convention of ‘not reading’ within the digital humanities, in which historical texts themselves can be marginalized or effaced altogether by the superabundance of information. As a supplement to this ‘distant’ reading, he goes on to demonstrate the potential of the latest machine-learning technologies to render significant volumes of transcription meaningful via text mining and the automated creation of patterns, frequencies, statistical models, and other forms of ‘mediated’ or ‘directed’ reading. He then demonstrates each kind of approach within a rich series of examples drawn from his work with the ARTFL Encyclopédie Project and the Electronic Enlightenment corpus, before concluding his analysis by presenting – with caveats – some preliminary radial visualizations of textual influence generated using the D3 JavaScript library.